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lpips_2dirs_allpairs.py compares each image in the first directory against every image in the second one.

lpips_2dirs_allpairs.py

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+import argparse
+import os
+import lpips
+import numpy as np
+
+parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+parser.add_argument('-d0','--dir0', type=str, default='./imgs/ex_dir0')
+parser.add_argument('-d1','--dir1', type=str, default='./imgs/ex_dir1')
+parser.add_argument('-o','--out', type=str, default='./imgs/example_dists.txt')
+parser.add_argument('-v','--version', type=str, default='0.1')
+parser.add_argument('--all-pairs', action='store_true', help='turn on to test all N(N-1)/2 pairs, leave off to just do consecutive pairs (N-1)')
+parser.add_argument('-N', type=int, default=None)
+parser.add_argument('--use_gpu', action='store_true', help='turn on flag to use GPU')
+
+opt = parser.parse_args()
+
+## Initializing the model
+loss_fn = lpips.LPIPS(net='alex',version=opt.version)
+if(opt.use_gpu):
+ loss_fn.cuda()
+
+# crawl directories
+f = open(opt.out,'w')
+files0 = os.listdir(opt.dir0)
+files1 = os.listdir(opt.dir1)
+
+dists = []
+for file0 in files0:
+ for file1 in files1:
+ img0 = lpips.im2tensor(lpips.load_image(os.path.join(opt.dir0,file0))) # RGB image from [-1,1]
+ if(opt.use_gpu):
+ img0 = img0.cuda()
+ img1 = lpips.im2tensor(lpips.load_image(os.path.join(opt.dir1,file1)))
+ if(opt.use_gpu):
+ img1 = img1.cuda()
+
+ # Compute distance
+ dist = loss_fn.forward(img0,img1)
+ print('(%s,%s): %.3f'%(file0,file1,dist))
+ f.writelines('(%s,%s): %.6f\n'%(file0,file1,dist))
+
+ dists.append(dist.item())
+
+avg_dist = np.mean(np.array(dists))
+stderr_dist = np.std(np.array(dists))/np.sqrt(len(dists))
+
+print('Avg: %.5f +/- %.5f'%(avg_dist,stderr_dist))
+f.writelines('Avg: %.6f +/- %.6f'%(avg_dist,stderr_dist))
+
+f.close()